Computer systems often are used to manage and process business data. To do so, a business enterprise may use various application programs running on one or more computer systems. Application programs may be used to process business transactions, such as taking and fulfilling customer orders, providing supply chain and inventory management, performing human resource management functions, and performing financial management functions. Data used in business transactions may be referred to as transaction data, transactional data or operational data. Often, transaction processing systems provide real-time access to data, and such systems may be referred to as on-line transaction processing (OLTP) systems.
Application programs also may be used for analyzing data, including analyzing data obtained through transaction processing systems When data used for analysis is produced in a different computer system than the computer system used for analysis or when a large volume of data is used for analysis, the use of an analysis data repository separate from the transaction computer system may be helpful. An analysis data repository may store data obtained from transaction processing systems and used for analytical processing. The analysis data repository may be referred to as a data warehouse, a data mart or an operational data store (ODS).
The term “data mart” typically is used when an analysis data repository stores data for a portion of a business enterprise or stores a subset of data stored in another, larger analysis data repository, which typically is referred to as a data warehouse. For example, a business enterprise may use a sales data mart for sales data and a financial data mart for financial data.
An ODS is designed to enable numerous queries on small amounts of granular data that are updated frequently. An ODS stores detailed data and typically supports tactical, day-to-day decision making. An ODS is important because front line areas of a business may rely on up-to-date, accurate information.
Many application programs, including transaction application programs and analytical application programs that use data warehouses, support alerting mechanisms that inform a user about something to which the user should attend or about which the user should be made aware. For example, an alert may be sent to a sales campaign manager when a deviation between planned and actual figures beyond a predefined threshold occurs. Similarly, an alert may be sent to a sales manager if the manager's pending sales opportunities indicate that the manager may not meet sales targets without action or intervention. Such alerting mechanisms may be particularly important for the user in a data rich environment where it is difficult to find out which information merits immediate attention.